On the scalability of hypergraph models for sparse matrix partitioning

Bora Uçar 1, 2 Umit Catalyurek 3
1 GRAAL - Algorithms and Scheduling for Distributed Heterogeneous Platforms
Inria Grenoble - Rhône-Alpes, LIP - Laboratoire de l'Informatique du Parallélisme
2 LIP - Laboratoire de l'Informatique du Parallélisme
3 Department of Biomedical Informatics [Columbus]
Abstract : We investigate the scalability of the hypergraph-based sparse matrix partitioning methods with respect to the increasing sizes of matrices and number of nonzeros. We propose a method to rowwise partition the matrices that correspond to the discretization of two-dimensional domains with the five-point stencil. The proposed method obtains perfect load balance and achieves very good total communication volume. We investigate the behaviour of the hypergraph-based rowwise partitioning method with respect to the proposed method, in an attempt to understand how scalable the former method is. In another set of experiments, we work on general sparse matrices under different scenarios to understand the scalability of various hypergraph-based one- and two-dimensional matrix partitioning methods.
Keywords : Sparse matrix-vector multiplication Matrix partitioning Hypergraph partitioning Sparse matrix-vector multiplication.
Type de document :
Communication dans un congrès
M. Danelutto, J. Bourgeois, and T. Gross. 18th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP 2010), Feb 2010, Pisa, Italy. IEEE, pp.593-600, 2010, 〈10.1109/PDP.2010.92〉
Liste complète des métadonnées

Littérature citée [9 références]  Voir  Masquer  Télécharger
https://hal-ens-lyon.archives-ouvertes.fr/ensl-00529088
Contributeur : Bora Uçar <>
Soumis le : dimanche 24 octobre 2010 - 19:28:44
Dernière modification le : vendredi 20 avril 2018 - 15:44:24
Document(s) archivé(s) le : vendredi 26 octobre 2012 - 12:15:29

Fichier

ucca10.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

INRIA | LIP | INSMI | ENS-LYON | UNIV-LYON1

Citation

Bora Uçar, Umit Catalyurek. On the scalability of hypergraph models for sparse matrix partitioning. M. Danelutto, J. Bourgeois, and T. Gross. 18th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP 2010), Feb 2010, Pisa, Italy. IEEE, pp.593-600, 2010, 〈10.1109/PDP.2010.92〉. 〈ensl-00529088〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

396

Téléchargements de fichiers

149

Contact

support.ccsd.cnrs.fr
hal.support@ccsd.cnrs.fr
Logo CCSD